Tensorflow 1.14.0 API Deprecation Warnings

[MajorError]

Tensorflow is deprecating the v1 API, and moving it into tf.compat.v1. In addition, some elements of the API are being replaced by new API.

Example output:

W0703 09:23:51.102508 140059022907200 deprecation.py:323] From site-packages/tensorflow/python/training/queue_runner_impl.py:391: QueueRunner.__init__ (from tensorflow.python.training.queue_runner_impl) is deprecated and will be removed in a future version.
Instructions for updating:
To construct input pipelines, use the `tf.data` module.
W0703 09:23:51.141032 140059022907200 deprecation.py:323] From site-packages/tensorflow/python/training/saver.py:1276: checkpoint_exists (from tensorflow.python.training.checkpoint_management) is deprecated and will be removed in a future version.
Instructions for updating:
Use standard file APIs to check for files with this prefix.
2019-07-03 09:23:52.959783: W tensorflow/compiler/jit/mark_for_compilation_pass.cc:1412] (One-time warning): Not using XLA:CPU for cluster because envvar TF_XLA_FLAGS=--tf_xla_cpu_global_jit was not set.  If you want XLA:CPU, either set that envvar, or use experimental_jit_scope to enable XLA:CPU.  To confirm that XLA is active, pass --vmodule=xla_compilation_cache=1 (as a proper command-line flag, not via TF_XLA_FLAGS) or set the envvar XLA_FLAGS=--xla_hlo_profile.
W0703 09:23:53.422218 140059022907200 deprecation_wrapper.py:119] From site-packages/mtcnn/mtcnn.py:187: The name tf.ConfigProto is deprecated. Please use tf.compat.v1.ConfigProto instead.

W0703 09:23:53.422743 140059022907200 deprecation_wrapper.py:119] From site-packages/mtcnn/mtcnn.py:193: The name tf.Session is deprecated. Please use tf.compat.v1.Session instead.

W0703 09:23:53.433550 140059022907200 deprecation_wrapper.py:119] From site-packages/mtcnn/network.py:43: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.

W0703 09:23:53.434048 140059022907200 deprecation_wrapper.py:119] From site-packages/mtcnn/layer_factory.py:88: The name tf.placeholder is deprecated. Please use tf.compat.v1.placeholder instead.

W0703 09:23:53.435072 140059022907200 deprecation_wrapper.py:119] From site-packages/mtcnn/layer_factory.py:79: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.

W0703 09:23:53.435565 140059022907200 deprecation.py:506] From site-packages/tensorflow/python/ops/init_ops.py:1251: calling VarianceScaling.__init__ (from tensorflow.python.ops.init_ops) with dtype is deprecated and will be removed in a future version.
Instructions for updating:
Call initializer instance with the dtype argument instead of passing it to the constructor
W0703 09:23:53.454373 140059022907200 deprecation_wrapper.py:119] From site-packages/mtcnn/layer_factory.py:171: The name tf.nn.max_pool is deprecated. Please use tf.nn.max_pool2d instead.

W0703 09:23:53.505696 140059022907200 deprecation.py:323] From site-packages/mtcnn/layer_factory.py:221: div (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Deprecated in favor of operator or tf.math.divide.
W0703 09:23:53.700929 140059022907200 deprecation_wrapper.py:119] From site-packages/mtcnn/layer_factory.py:196: The name tf.nn.xw_plus_b is deprecated. Please use tf.compat.v1.nn.xw_plus_b instead.

This issue is distinct from #3, which refers to the keep_dims deprecation.

I understand that I can filter warnings to suppress them, but sometimes they contain useful notifications that are relevant elsewhere in my codebase, so I'd prefer not to if I can help it!

Is there a roadmap to migrate to non-deprecated Tensorflow APIs?

[superSupa]

I am facing with this too
Please guide me if you found the solution
Thank you~

[jack-kavanagh]

Also having this problem

[noiji]

You can see the solution here. Upgrading code is noted. https://www.tensorflow.org/beta/guide/upgrade

[tangjie77wd]

@jack-kavanagh Have you upgraded Tensorflow to version 2.0 ?Have already solved the problem?

[jack-kavanagh]

@tangjie77wd yes I fixed the issue by upgrading to TF 2.0

[tangjie77wd]

@jack-kavanagh My Tensorflow version is 1.13 and i use pip --upgrade tensorflow but get nothing.How do you upgrade Tensorflow ? I really do not want build Tensorflow totally again because the process is painful for me so i just want to upgrade it.

[jack-kavanagh]

@tangjie77wd I tried to use pip --upgrade tensorflow, but this didn't help. I ended up using pip install tensorflow==2.0.0-beta1 (tensorflow-gpu==2.0.0-beta1) for the gpu version.

[tangjie77wd]

@jack-kavanagh Thank you very much ! I have test "pip install tensorflow==2.0.0-beta1" for my cpu version successfully because it outputs 2.0.0-beta1 when i inputs print(tf.version). However,the warning is still the same when i run my tensorflow c++ project .By the way ,i have not changed anything of my tensorflow c++ project because i do not know what should be replaced . Do i need change something like the project properties or active something since i have upgrade tensorflow from 1.13.1 to 2.0.0 ?

[ganesh-ms]

The below link solved my issue.

https://stackoverflow.com/a/56820328/6825288

[cnopens]

only adjust "import compat.v1.tensorflow as tf"